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International Journal of Computer Applications (0975 – 8887)
Volume 142 – No.5, May 2016
33
Development of a portable DAQ-based
Electroencephalogram System
Saeed Mohsen Ain Shams University
Cairo, Egypt
Abdelhalim Zekry Ain Shams University
Cairo, Egypt
Mohamed Abouela Ain Shams University
Cairo, Egypt
Ahmed Elshazly ElGezeera Academy
Cairo, Egypt
ABSTRACT
This paper presents a virtual electronic system for measuring
the EEG signals. The system consists of electrodes, an
instrumentation amplifier, filters and a DAQ card with
LabVIEW application on a personal computer. The system is
developed for displaying, measuring, analyzing and recording
the EEG signals. The system is practically implemented with
success where the experimental results are verified with
simulation results.
Keywords
Electroencephalogram (EEG), Data Acquisition (DAQ),
Laboratory Virtual Instruments Engineering Workbench
(LabVIEW).
1. INTRODUCTION The EEG is important in the medical field. The EEG is used
to record the brain activities that are used in diagnoses
strokes. Recently, the advancement in technology of the brain
signals enabled the control of equipment that could help the
humans in their daily life such as wheelchair and robots. Now,
mindwave and emotive epock are used in EEG systems.
Berger is the inventor of electroencephalography and
discoverer of the alpha wave rhythm. Many EEG acquisition
systems were developed [1-5]. Most of these systems are used
to monitor the patient suffering from clinical disorder related
to the brain [6-8]. This requires that the patient to be in health
care center under the constant supervision for diagnoses [9,
10]. Hence, the EEG system is developed in order to be
portable. The portability is in the first step is based utilizing a
data acquisition card DAQ and laptop. The EEG system is a
low cost system, since LabVIEW plotter application is
developed the EEG system. So, the main target is to design
and implement a light weight EEG system with three
electrodes. These electrodes are used to sense the signals on
human brain which are produced by neurons. The main
problems with the brain electrical signals are that they are
very small (10u V-100u V) [11]. So, they have to be amplified
with special amplifiers. Such amplifiers are called
instrumentation amplifiers. These amplifiers are characterized
by high gain and common mode rejection ratio in addition to
high input impedance. With these specifications, human brain
signals can be amplified to get the EEG signal. The filter
circuits are also required to clean the contamination and
artifacts in EEG signal. The EEG system is implemented
based on our design with DAQ card and computer. The paper
is organized as follows: in section 2, the EEG system design
will be presented. Then in section 3, the practical
implementation of EEG circuits will be introduced. In section
4, the LabVIEW software implementation will be described in
detail. Section 5 presents the experimental results and the
conclusion is described in section 6.
2. DESIGNING OF AN EEG SYSTEM The block diagram of the EEG system is shown in Figure 1.It
consists of electrodes to access the brain signal, an
instrumentation amplifier to amplify the accessed signal,
Filter to limit the bandwidth of the accessed brain signal, a
gain block to achieve proper signal strength for displaying and
recording, A DAQ card to acquire the signal for a laptop or a
pc. In the next subsections, these components will be
described in detail.
Fig 1: Block diagram of EEG system.
2.1 EEG Electrodes In order to measure and record the potential from the body, it
is necessary to provide interface between body and potential
measuring electronics apparatus. The EEG signal from the
brain is taken using electrodes placed on the scalp region of
head. The electrodes used for this acquisition are made up of
Ag-AgCl [12].
2.2 Instrumentation Amplifier The instrumentation amplifier circuit is shown in Figure 2.
After accessing the brain signal by the appropriate electrodes,
AD620 has been used as an instrumentation amplifier. The
amplifier chip AD620 has Gain reaching to 10000 and its
CMMR is 100 dB. The gain of this amplifier can be calculated
by using the formula: G= (1+ (49.4 KΩ / R3)). Hence, the gain
can be adjusted by changing R3. Here R3 is selected to be 470
Ω so, to achieve gain nearly equals 107.
Fig 2: Instrumentation Amplifier.
International Journal of Computer Applications (0975 – 8887)
Volume 142 – No.5, May 2016
34
2.3 Band pass filter & Gain stage The bandpass filter circuit is depicted in Figure 3. It is a
simple one stage high pass C-R filter followed by a lossy
integrator acting as a low pass filter and gain block. High pass
cut-off frequency is roughly 0.5 Hz and low pass filter cut-off
frequency is nearly 34 Hz [13, 14]. The frequency response of
designed circuit is shown in Figure 4. The midband gain of
100 and the 3-dB cut off points of 0.35 Hz and 24 Hz.
Fig 3: Band pass filter and gain stage.
Fig 4: Frequency response of designed circuit.
2.4 Power Management Circuit The analog electronic part of the interface circuit must be
supplied with the proper power supply. May be the best power
supply to avoid interference with the public supply is to use
chemical rechargeable batteries. In addition, this system is
aimed to develop a portable instrumentation. The power
supply range for operational amplifiers is selected to be in low
voltage range which can be supplied by small batteries. So,
this circuit is designed to work on the voltage range of above
three volts and under 5V. Also, there is a need to supply
constant power supply to the operational amplifiers since the
battery voltage is degraded with continuous usage. Hence, a
constant ± 5V power is extracted from a 9V battery using
5Vvoltage regulators. Two 9V rechargeable Batteries are used to supply power to the circuit by connecting them in series as
shown in Figure 5. The positive terminal of one battery and
negative terminal of another battery are connected together to
form a zero voltage ground terminal. The capacitors are used
on either side of the regulator to supply clean DC power to the
operational amplifiers. The 9V power supplies are regulated
using UA7805 for 5V and UA7905 for -5 V to provide a
constant power supply voltage to the operational amplifiers.
The whole power supply circuit is shown in Figure 5.
Fig 5: Power supply circuit schematic diagram.
2.5 Data Acquisition The function of data acquisition is to acquire an electrical or
physical phenomenon such as voltage. Also, Data Acquisition
is the process of analyzing and saving the data. Data
Acquisition card (DAQ) acts as connection between the
computer and the outside world. It functions as a device that
digitalizes incoming analog signals that are interpreted by the
computer. There are different types for DAQ cards. The 6008
DAQ card is satisfactory for purposes while cost effective.
This DAQ card is provided by National Instruments and has
some properties as small size, compatible with LabVIEW,
eight analog inputs, two analog outputs, 12 digital I/O and
USB connection. Also, the 6008 DAQ card has 12 bit
resolution.
3. EEG CIRCUIT IMPLEMENTATION After simulating the circuit is verified by bread board until
satisfactory results were achieved. The final EEG circuit is
laid out on a printed circuit board by using ARES software.
The circuit lay out is shown in Figure 6 while Figure 7 shows
The EEG circuit is construction on PCB. The power supply
circuit is fully constructed as shown in Figure 8.
Fig 6: Final design by using ARES Software.
Printing the circuit to a PCB helps reduce some noise in the
EEG system and allow for a much smaller product as shown
in Figure 6. Only four resistors, two capacitors, two integrated
circuits and three electrodes are used in our EEG circuit
implementation.
International Journal of Computer Applications (0975 – 8887)
Volume 142 – No.5, May 2016
35
Fig 7: Final PCB construction of EEG circuit. Fig 8: Construction of power supply circuit.
4. LABVIEW SOFTWARE PLOTTER
DEVELOPMENT In this section, the developed plotter application on the
LabVIEW will be described. LabVIEW is graphical
programming language which uses blocks instead of lines of
text to create programs. LabVIEW is produced by National
instruments. The LabVIEW is installed on the windows
system which operates on a computer. The plotter application
is developed on LabVIEW whose block diagram is depicted
in Figure 9. It is developed for acquiring, controlling,
measuring, analyzing, processing and saving the EEG signals .
The DAQ Assistant block is used to read an analog input
signal from the DAQ card that receives the output of the EEG
circuit. The Configuration of the DAQ Assistant involves
setting the expected input range to the DAQ device and
sampling rate. The DAQ Assistant express block includes
options for setting which hardware channel to use and
selecting the acquisition mode of the device. There are four
blocks which are developed for displaying the signals.
The DAQ Assistant block wired to one of them as Waveform
graph to observe the EEG signal in time domain. The vertical
pointer slide control placed and wired it to the y terminal of
multiply function to adjust the gain. The maximum range of
the vertical pointer slide control is five for the gain changing.
Also, a filter block is created to smooth the incoming data.
The Write to Measurement file block is used to save the data
in a file. The configuration of the Write to Measurement
expresses the file name text box that contains the full path to
the output file. LabVIEW saves data with up to six digits of
precision in .lv m file. The FFT blocks are developed to
transform the data in the frequency domain because it is easier
to analyze the EEG signal originally in time domain, in the
frequency domain. The presence of specific frequencies is an
indicator of different brain states such as resting and sleeping
[11]. The graphical user interface panel based on LabVIEW
plotter application developed in Figure 9 is depicted in Figure
10 where it shows the virtual instrument controls and displays.
Fig 9: LabVIEW block diagram.
This panel consists of two buttons. One button is (stop (F))
that is used to stop the running and displays the final status on
the screen. The other button is (save to file) that is used to
save the acquired data from the connected device. There are
two vertical pointer slides used to change the signal gain.
Also, two waveform graphs are created to display the output
signals in time domain on the front panel. Moreover, two FFT
spectrum graphs are created to display the frequency spectrum
of the brain signals.
International Journal of Computer Applications (0975 – 8887)
Volume 142 – No.5, May 2016
36
Fig 10: EEG plotter control and display panel on a Computer.
5. EXPERIMENTAL RESULTS Now to demonstrate the ordinary operation of our virtual
instrument based EEG system, it is used to display and
process the acquired EEG signal from a normal person.
Therefore, figure 11 shows typical recording of EEG raw
signals for 1 second at sampling rate 1k samples.
Fig 11: EEG signal for 1 second at 1k samples.
Figure 12 depicts the fast Fourier transform of the EEG wave
from shown in Figure 11. It is clear from the figure that the
amplitude of the frequency components decrease with time as
observed with ordinary EEG signals.
Fig 12: spectrum of raw EEG signals at 1k samples
In order to see the effect of the sampling on the EEG signal
acquisition process, figure 13 shows the recording of EEG
signals for 0.5 second at sampling rate of 2k samples.
Fig 13: EEG signal for 0.5 second at 2k samples.
The frequency spectrum of the EEG signal sampled at the
double rate seems smoother than that at lower sampling rate.
As shown in Figure 14. But, they almost have the same shape.
This is because the lower sampling rate is much higher than
International Journal of Computer Applications (0975 – 8887)
Volume 142 – No.5, May 2016
37
the Nyquist sampling rate which is double the highest
frequency contained in the EEG signal. The highest frequency
of the EEG signal is limited to 34 Hz.
Fig 14: spectrum of raw EEG signals at 2k samples.
In order to see the effect of the digital filter on the EEG signal,
figure 15 shows the filtered EEG signals for 0.5 second at
sampling rate 2k samples. The digital filter used is a third
order FIR low pass filter and is characterized by cut off
frequency of 34 Hz. The magnitude response of the digital
filter is shown in Figure 16. It is clear that the filter has great
effect on the shape of the waveform where the signal
approaches the sinusoidal waveform.
Fig 15: filtered EEG signals for 0.5 second at sampling
rate 2k samples.
Fig 16: The magnitude response of the Low pass FIR
digital filter.
Finally, Figure 17 shows a comparison between these results
and the results given in referece [15]. The two signals
resembles each other to great extent in spit of belonging to
different persons.
(a)
International Journal of Computer Applications (0975 – 8887)
Volume 142 – No.5, May 2016
38
(b)
Fig 17: Comparison between two EEG rhythms: (a) recorded rhythm, (b) published rhythm in paper [15].
6. CONCLUSIONS & FUTURE WORK This paper introduces a full operational and low cost
electronic system for acquiring and processing the EEG
signals. The developed system consists of an analog circuit
that interfaces a data acquisition card connected to Lap Top or
PC. The software required to operate the setup is developed
using LabVIEW in time domain and frequency domain. The
developed setup is tested and proved to work properly. In this
way one can develop an economical reliable test equipment
for biomedical applications which can displace the very
expensive instruments. Also, one can extend the system for
multiple probe operation.
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